Using Matplotlib

# required imports

import pandas as pd
import seaborn as sns
import geopandas as gpd
import matplotlib.pyplot as plt

sns.set_style('whitegrid')

#Reading the shape file
fp = r'C:\Users\pc\Desktop\chloropleth\india-polygon.shp'
map_df = gpd.read_file(fp)
map_df.head()

	id	st_nm	geometry
0	None	Andaman and Nicobar Islands	MULTIPOLYGON (((93.84831 7.24028, 93.92705 7.0...
1	None	Arunachal Pradesh	POLYGON ((95.23643 26.68105, 95.19594 27.03612...
2	None	Assam	POLYGON ((95.19594 27.03612, 95.08795 26.94578...
3	None	Bihar	POLYGON ((88.11357 26.54028, 88.28006 26.37640...
4	None	Chandigarh	POLYGON ((76.84208 30.76124, 76.83758 30.72552...

#Reading the excel
data_df = pd.read_excel(r'C:\Users\pc\Desktop\chloropleth\data_ecxel.xlsx')
data_df.head()

	S. No.	Name of State / UT	Total Confirmed cases	Cured/Discharged/	Death
0	1	Andaman and Nicobar Islands	12	11	0
1	2	Andhra Pradesh	603	42	15
2	3	Arunachal Pradesh	1	0	0
3	4	Assam	35	9	1
4	5	Bihar	85	37	2

#Merging the data
merged = map_df.set_index('st_nm').join(data_df.set_index('Name of State / UT'))
merged.head()

	id	geometry	S. No.	Total Confirmed cases	Cured/Discharged/	Death
st_nm
Andaman and Nicobar Islands	None	MULTIPOLYGON (((93.84831 7.24028, 93.92705 7.0...	1.0	12.0	11.0	0.0
Arunachal Pradesh	None	POLYGON ((95.23643 26.68105, 95.19594 27.03612...	3.0	1.0	0.0	0.0
Assam	None	POLYGON ((95.19594 27.03612, 95.08795 26.94578...	4.0	35.0	9.0	1.0
Bihar	None	POLYGON ((88.11357 26.54028, 88.28006 26.37640...	5.0	85.0	37.0	2.0
Chandigarh	None	POLYGON ((76.84208 30.76124, 76.83758 30.72552...	6.0	21.0	9.0	0.0

# create figure and axes for Matplotlib and set the title
fig, ax = plt.subplots(1, figsize=(10, 10))
ax.axis('off')
ax.set_title('Deaths', fontdict={'fontsize': '25', 'fontweight' : '10'})

# plot the figure
merged.plot(column='Total Confirmed cases',cmap='YlOrRd', linewidth=0.8, ax=ax, edgecolor='0', legend=True,markersize=[39.739192, -104.990337])

Using GeoPlot

import geopandas as gdp
import geoplot as gplt
import geoplot.crs as gcrs

gplt.polyplot(merged)

gplt.choropleth(
    merged, hue='Total Confirmed cases', projection=gcrs.AlbersEqualArea(),
    edgecolor='black', linewidth=1,
    cmap='YlOrRd', legend=True
)

Using Folium

import folium as flm
from folium import plugins
import ipywidgets
import geocoder
import geopy
import numpy as np
import pandas as pd

import json

# load geo_json
# shapefiles can be converted to geojson with QGIS
with open(r'C:\Users\pc\Desktop\chloropleth\GeoJson-Data-of-Indian-States-master\Indian_States') as f:
    geojson_counties = json.load(f)

for i in geojson_counties['features']:
    i['id'] = i['properties']['NAME_1']
    
# load data associated with geo_json
pop_df = pd.read_excel(r'C:\Users\pc\Desktop\chloropleth\data_ecxel.xlsx')
pop_df.head()

	S. No.	Name of State / UT	Total Confirmed cases	Cured/Discharged/	Death
0	1	Andaman and Nicobar Islands	12	11	0
1	2	Andhra Pradesh	603	42	15
2	3	Arunachal Pradesh	1	0	0
3	4	Assam	35	9	1
4	5	Bihar	85	37	2

map1 = flm.Map(location=[20.5937,78.9629], zoom_start=4)

flm.Choropleth(
    geo_data=geojson_counties,
    name='choropleth',
    data=pop_df,
    columns=['Name of State / UT', 'Total Confirmed cases'],
    # see folium.Choropleth? for details on key_on
    key_on='feature.id',
    fill_color='YlGn',
    fill_opacity=0.5,
    line_opacity=0.5).add_to(map1)

# layer control to turn choropleth on or off
flm.LayerControl().add_to(map1)

# display map
map1